长江科学院院报Issue(4)：12-17,6.DOI:10.3969/j.issn.1001-5485.2015.04.003
回归支持向量机集成模型在年径流预测中的应用
Application of SVR Ensemble Model to Annual Runoff Forecasting
代兴兰1
作者信息
- 1. 云南省水文水资源局 曲靖分局，云南 曲靖 655000
- 折叠
摘要
Abstract
An ensemble model involving different impact factors (input vectors)based on support vector regression (SVR)is put forward to improve runoff prediction accuracy and generalization ability.The runoff at Nanpanjiang west bridge station in Yunnan from 1961 to 2007 is taken as a case study.First,a number of impact factors for annual run-off forecast are selected to build different models for the study of a single instance of SVR,and the corresponding RBF models are built as a comparison.In subsequence,the results of single models (which are accurate and comple-mentary)are integrated by using weighted average and simple average respectively.Results showed that:the average relative absolute error of weighted average and simple average ensemble model based on SVR was respectively 1.27%and 1.54%,and the maximum relative absolute error is 2.99% and 2.74%.The accuracy and generalization capa-bilities are significantly superior to the single models as well as the weighted average and simple average ensemble model based on RBF models.The weighted average ensemble model based on SVR has better accuracy and generali-zation capability than simple average because it gives more weight to the models with good prediction result.关键词
径流预测/集成模型/回归支持向量机/加权平均/简单平均Key words
runoff forecasting/ensemble model/SVR/weighted average/simple average分类
天文与地球科学引用本文复制引用
代兴兰..回归支持向量机集成模型在年径流预测中的应用[J].长江科学院院报,2015,(4):12-17,6.
